{"id":"W2014517001","doi":"10.1142/s0218213004001697","title":"TEMPORAL VERSUS LATEST SNAPSHOT WEB USAGE MINING USING KOHONEN SOM AND MODIFIED KOHONEN SOM BASED ON THE PROPERTIES OF ROUGH SETS THEORY","year":2004,"lang":"en","type":"article","venue":"International Journal of Artificial Intelligence Tools","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"","keywords":"Self-organizing map; Computer science; Cluster analysis; Web mining; Data mining; Snapshot (computer storage); The Internet; Hierarchical clustering; Rough set; Artificial intelligence; Web page; Database; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001022423,0.0001637725,0.0002056764,0.0001902484,0.0001581747,0.000454687,0.001314508,0.00005622653,0.00002842041],"category_scores_gemma":[0.0004073474,0.0001164455,0.0001029743,0.0002221231,0.000221447,0.0008113187,0.0001751325,0.0002351808,0.000007975276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000935197,"about_ca_system_score_gemma":0.0003118209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007615377,"about_ca_topic_score_gemma":0.00001586796,"domain_scores_codex":[0.9981396,0.00009524613,0.0007040223,0.0002356191,0.0006343268,0.0001912152],"domain_scores_gemma":[0.9982052,0.0004782098,0.0005272213,0.0002928914,0.0004188529,0.00007756843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001418318,0.001136622,0.0003243414,0.00002662493,0.000479945,0.0001532695,0.008089473,0.2662719,0.07326298,0.2826014,0.0001726379,0.3660625],"study_design_scores_gemma":[0.000428529,0.000451396,0.0002438331,0.0005806229,0.00004114002,0.00007397459,0.00117783,0.8479075,0.1246313,0.02383959,0.0002942032,0.0003299757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7072183,0.00009220052,0.2875245,0.003844919,0.0008227129,0.0001607565,0.00003923996,0.0000180576,0.0002792862],"genre_scores_gemma":[0.9629719,0.0000179453,0.03659316,0.0001960183,0.0001918692,0.000005212384,0.000005647595,0.00001036641,0.000007903182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5816357,"threshold_uncertainty_score":0.474851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1691226850754209,"score_gpt":0.3320782916227807,"score_spread":0.1629556065473598,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}